A Fuzzy-Based Histogram Analysis Technique for Skin Lesion Discrimination in Dermatology Clinical Images

Author

R. Joe Stanley, Missouri University of Science and TechnologyFollow
Ramos H. Moss
William V. Stoecker, Missouri University of Science and TechnologyFollow
Chetna Aggawal

Abstract

A fuzzy logic-based color histogram analysis technique is presented for discriminating benign skin lesions from malignant melanomas in dermatology clinical images. The approach utilizes a fuzzy set for benign skin lesion color, and alpha-cut and support set cardinality for quantifying a fuzzy ratio skin lesion color feature. Skin lesion discrimination results are reported for the fuzzy ratio and fusion with a previously determined percent melanoma color feature over a data set of 258 clinical images. For the fusion technique, alpha-cuts for the fuzzy ratio can be chosen to recognize over 93.30% of melanomas with approximately 15.67% false positive lesions.

Recommended Citation

R. J. Stanley et al., "A Fuzzy-Based Histogram Analysis Technique for Skin Lesion Discrimination in Dermatology Clinical Images," Computerized Medical Imaging and Graphics, vol. 27, no. 5, pp. 387 - 396, Elsevier, Sep 2003.

The definitive version is available at https://doi.org/10.1016/S0895-6111(03)00030-2

Department(s)

Electrical and Computer Engineering

Second Department

Chemistry

Keywords and Phrases

Approximation Theory; Algorithms; Benign Tumor; Clinical Feature; Color Histogram Analysis; Computer Assisted Diagnosis; Dermatology; Diagnosis; Diagnostic Accuracy; Diagnostic Imaging; Diagnostic Value; Differential Diagnosis; Fuzzy Logic; Fuzzy Sets; Humans; Image Analysis; Malignant Melanoma; Medical Imaging; Model; Priority Journal; Skin Defect; Skin Neoplasms; Skin Pigmentation; Skin Tumor

International Standard Serial Number (ISSN)

0895-6111

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2003 Elsevier, All rights reserved.

Publication Date

01 Sep 2003